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![Do we need multi-level analysis?
• “[A] limitation of [common learning gains approaches] is that general linear
models are based on the assumption that observed data of one student are
independent of observed data of another. This assumption is not true in
situations where students from the same discipline, identical module, and
same university have similar experiences (e.g., easy assessment in week 1,
difficult assessment in week 6, and moderately hard final assessment in week
15) which means the variance in their scores are not independent and are
linked. This means that simple linear models to measure learning gains may
provide inaccurate and misleading outcomes.” (Rogaten et al., paper 2)](https://image.slidesharecdn.com/presentation6brientiesdiscussion-161208184945/75/Discussant-SRHE-Symposium-A-cross-institutional-perspective-on-merits-and-challenges-of-learning-gains-for-Teaching-Excellence-Framework-7-2048.jpg)
Uploaded byBart Rienties
Discussant SRHE Symposium "A cross-institutional perspective on merits and challenges of learning gains for Teaching Excellence Framework"
The document discusses the complexities and challenges of measuring learning gains from a cross-institutional perspective, highlighting various conceptualizations and methodological approaches. It emphasizes the need for coherence in understanding and measuring learning gains, addressing issues such as individual differences and varying contexts. The ABC project, involving multiple contributors, aims to further explore these themes and methodologies in the context of teaching excellence.
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Discussant SRHE Symposium "A cross-institutional perspective on merits and challenges of learning gains for Teaching Excellence Framework"
- 1. Discussion: A cross-institutional perspectiveon merits and challenges of learning gains for Teaching Excellence Framework Bart Rienties https://twitter.com/LearningGains https://abclearninggains.com/ The results of the ABC project were made possible due to Jekaterina Rogaten, Bart Rienties, Simon Cross, Ceri Hitching, Ian Kinchin, Simon Lygo-Baker, Allison Littlejohn, Ian Scott, Rhona Sharpe, Steve Warburton, and Denise Whitelock. Please contract Jekaterina.rogaten@open.ac.uk if you want to know more about ABC learning gains
- 2. Learning gains isa complex topic
- 3. Learning gains isa complex topic
- 4. Learning gains: differentconceptualisations • Conceptualisation of learning gains substantially different across the five papers • From private vs public • From affective to cognitive • From during a degree until employment • From student or staff perspective
- 5. Learning gains: differentmethods and approaches • Qualitative • Interviews (Paper 1, 4, 5) • Sorting exercise (Paper 4) • Personal reflections (Paper 1) • Quantitative (Paper 3, 2) • (Affective) survey instruments (Paper 3) • Grades/degree outcomes (Paper 3, 2) • Different level of analysis • Thematic analysis • Semi-structured interviews • ANOVA/correlations (Paper 3) • Regressions and Multi-level modelling (Paper 3, 2) • Longitudinal (Paper 2, 3, 5) • Randomised Control Trials (Paper 5) vs convenience sampling
- 6. Do we needfine-grained techniques? • “I learned nothing in College. Ok, ok, maybe that’s an exaggeration. I learned some things in college. I learned that I can’t stomach cheap beer; I’d rather play drinking games with a box of wine. I learned what kind of guys I should never date again. I learned how to live with kids my own age and quite frankly I do best living alone. Most importantly, I met two English professors who had a huge impact on my life, who taught me not just how to write but also to believe in myself. Meeting them made my college years worth it. For the most part, as I reflect on my undergraduate experience, I feel that it was a colossal waste of time. http://www.huffingtonpost.com/sarah-rose-attman/i-learned- nothing-in-coll_b_5606640.html. (Hughes, Paper 1)
- 7. Do we needmulti-level analysis? • “[A] limitation of [common learning gains approaches] is that general linear models are based on the assumption that observed data of one student are independent of observed data of another. This assumption is not true in situations where students from the same discipline, identical module, and same university have similar experiences (e.g., easy assessment in week 1, difficult assessment in week 6, and moderately hard final assessment in week 15) which means the variance in their scores are not independent and are linked. This means that simple linear models to measure learning gains may provide inaccurate and misleading outcomes.” (Rogaten et al., paper 2)
- 8. Need for coherence:questions to authors • Which learning gains? • Can we develop a common, shared perspective of what learning gains are? • How to measure learning gains? • What approaches and measurements are appropriate for capturing and measuring learning gains? • From apples to oranges to busses and e-cigarettes • How are we going to take into consideration individual differences (e.g., prior qualifications, socio-economic) and learning design differences (e.g., different assessments, support structures) when comparing learning gains? • How are we going to compare learning gains across different disciplines, contexts, and universities?
- 9. Discussion: A cross-institutional perspectiveon merits and challenges of learning gains for Teaching Excellence Framework Bart Rienties https://twitter.com/LearningGains https://abclearninggains.com/ The results of the ABC project were made possible due to Jekaterina Rogaten, Bart Rienties, Simon Cross, Ceri Hitching, Ian Kinchin, Simon Lygo-Baker, Allison Littlejohn, Ian Scott, Rhona Sharpe, Steve Warburton, and Denise Whitelock. Please contract Jekaterina.rogaten@open.ac.uk if you want to know more about ABC learning gains